import types
from typing import Literal, Optional, Union

import litellm


class FireworksAIConfig:
    """
    Reference: https://docs.fireworks.ai/api-reference/post-chatcompletions

    The class `FireworksAIConfig` provides configuration for the Fireworks's Chat Completions API interface. Below are the parameters:
    """

    tools: Optional[list] = None
    tool_choice: Optional[Union[str, dict]] = None
    max_tokens: Optional[int] = None
    temperature: Optional[int] = None
    top_p: Optional[int] = None
    top_k: Optional[int] = None
    frequency_penalty: Optional[int] = None
    presence_penalty: Optional[int] = None
    n: Optional[int] = None
    stop: Optional[Union[str, list]] = None
    response_format: Optional[dict] = None
    user: Optional[str] = None

    # Non OpenAI parameters - Fireworks AI only params
    prompt_truncate_length: Optional[int] = None
    context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = None

    def __init__(
        self,
        tools: Optional[list] = None,
        tool_choice: Optional[Union[str, dict]] = None,
        max_tokens: Optional[int] = None,
        temperature: Optional[int] = None,
        top_p: Optional[int] = None,
        top_k: Optional[int] = None,
        frequency_penalty: Optional[int] = None,
        presence_penalty: Optional[int] = None,
        n: Optional[int] = None,
        stop: Optional[Union[str, list]] = None,
        response_format: Optional[dict] = None,
        user: Optional[str] = None,
        prompt_truncate_length: Optional[int] = None,
        context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = None,
    ) -> None:
        locals_ = locals().copy()
        for key, value in locals_.items():
            if key != "self" and value is not None:
                setattr(self.__class__, key, value)

    @classmethod
    def get_config(cls):
        return {
            k: v
            for k, v in cls.__dict__.items()
            if not k.startswith("__")
            and not isinstance(
                v,
                (
                    types.FunctionType,
                    types.BuiltinFunctionType,
                    classmethod,
                    staticmethod,
                ),
            )
            and v is not None
        }

    def get_supported_openai_params(self):
        return [
            "stream",
            "tools",
            "tool_choice",
            "max_tokens",
            "temperature",
            "top_p",
            "top_k",
            "frequency_penalty",
            "presence_penalty",
            "n",
            "stop",
            "response_format",
            "user",
            "prompt_truncate_length",
            "context_length_exceeded_behavior",
        ]

    def map_openai_params(
        self,
        non_default_params: dict,
        optional_params: dict,
        model: str,
        drop_params: bool,
    ) -> dict:
        supported_openai_params = self.get_supported_openai_params()
        for param, value in non_default_params.items():
            if param == "tool_choice":
                if value == "required":
                    # relevant issue: https://github.com/BerriAI/litellm/issues/4416
                    optional_params["tools"] = "any"

            if param in supported_openai_params:
                if value is not None:
                    optional_params[param] = value
        return optional_params